diff --git a/invokeai/backend/install/model_install_backend.py b/invokeai/backend/install/model_install_backend.py
index c25d136855..8da0ab0bd2 100644
--- a/invokeai/backend/install/model_install_backend.py
+++ b/invokeai/backend/install/model_install_backend.py
@@ -201,7 +201,10 @@ class ModelInstall(object):
                 models_installed.update(self._install_path(path))
 
             # folders style or similar
-            elif path.is_dir() and any([(path/x).exists() for x in {'config.json','model_index.json','learned_embeds.bin'}]):
+            elif path.is_dir() and any([(path/x).exists() for x in \
+                                        {'config.json','model_index.json','learned_embeds.bin','pytorch_lora_weights.bin'}
+                                        ]
+                                       ):
                 models_installed.update(self._install_path(path))
 
             # recursive scan
diff --git a/invokeai/backend/model_management/model_manager.py b/invokeai/backend/model_management/model_manager.py
index 82f738894d..613779be9b 100644
--- a/invokeai/backend/model_management/model_manager.py
+++ b/invokeai/backend/model_management/model_manager.py
@@ -785,7 +785,7 @@ class ModelManager(object):
                     if path in known_paths or path.parent in scanned_dirs:
                         scanned_dirs.add(path)
                         continue
-                    if any([(path/x).exists() for x in {'config.json','model_index.json','learned_embeds.bin'}]):
+                    if any([(path/x).exists() for x in {'config.json','model_index.json','learned_embeds.bin','pytorch_lora_weights.bin'}]):
                         new_models_found.update(installer.heuristic_import(path))
                         scanned_dirs.add(path)
 
@@ -794,7 +794,8 @@ class ModelManager(object):
                     if path in known_paths or path.parent in scanned_dirs:
                         continue
                     if path.suffix in {'.ckpt','.bin','.pth','.safetensors','.pt'}:
-                        new_models_found.update(installer.heuristic_import(path))
+                        import_result = installer.heuristic_import(path)
+                        new_models_found.update(import_result)
 
             self.logger.info(f'Scanned {items_scanned} files and directories, imported {len(new_models_found)} models')
             installed.update(new_models_found)
diff --git a/invokeai/backend/model_management/model_probe.py b/invokeai/backend/model_management/model_probe.py
index af01e8d2e0..5aa9b6bdca 100644
--- a/invokeai/backend/model_management/model_probe.py
+++ b/invokeai/backend/model_management/model_probe.py
@@ -126,6 +126,8 @@ class ModelProbe(object):
                 return ModelType.Vae
             elif any(key.startswith(v) for v in {"lora_te_", "lora_unet_"}):
                 return ModelType.Lora
+            elif any(key.endswith(v) for v in {"to_k_lora.up.weight", "to_q_lora.down.weight"}):
+                return ModelType.Lora
             elif any(key.startswith(v) for v in {"control_model", "input_blocks"}):
                 return ModelType.ControlNet
             elif key in {"emb_params", "string_to_param"}:
@@ -136,7 +138,7 @@ class ModelProbe(object):
             if len(ckpt) < 10 and all(isinstance(v, torch.Tensor) for v in ckpt.values()):
                 return ModelType.TextualInversion
         
-        raise ValueError("Unable to determine model type")
+        raise ValueError(f"Unable to determine model type for {model_path}")
 
     @classmethod
     def get_model_type_from_folder(cls, folder_path: Path, model: ModelMixin)->ModelType:
@@ -166,7 +168,7 @@ class ModelProbe(object):
             return type
 
         # give up
-        raise ValueError("Unable to determine model type")
+        raise ValueError("Unable to determine model type for {folder_path}")
 
     @classmethod
     def _scan_and_load_checkpoint(cls,model_path: Path)->dict: